Star Wars

A famous quote by Han Solo:

“May the force be with you!”

Baked Tomato Sauce Recipe:

Ingredients:

• 5 tablespoons olive oil
• 1 pound very ripe cherry tomatoes, halved
• 1/3 cup plain dry bread crumbs, panko works great here
• 1/4 cup freshly grated Parmigiano-Reggiano cheese
• 2 tablespoons freshly grated pecorino cheese
• 2 garlic cloves, finely chopped *Salt and freshly ground pepper to taste
• 1 pound dried fusilli (corkscrew) or farfalline (butterfly) pasta
• 1/4 cup loosely packed fresh basil leaves, torn or sliced

“Special” kitchen tools required:

• Oven
• 13-by-9-inch baking dish
• Large pot

Steps:

1. Heat oven to 400 degrees Fahrenheit.
2. Pour 2 tablespoons of olive oil in bottom of 13-by-9-inch baking dish.
3. Arrange the tomatoes in the dish, cut side up
4. In smal bowl, cobine bread crumbs, cheeses, and garlic.
5. Toss mixture with a fork to mix well.
6. Sprinkle bread-crumb mixture over tomatoes, making sure that each cut side is well coevered with crumble mixture.
7. Bake for approximately 20 minutes, or until tomatoes are cooked through and crumbs are starting to brown on top.
8. While tomatoes are baking, bring a large pot of well-salted water to a boil.
9. Add pasta and cook for 8 to 10 minutes
10. When tomatoes are done, add basil
11. Use fork to stir and lightly mash tomatoes into a rough sauce.
12. Drain pasta and transfter to baking dish.
13. Add 2 tablespoons olive oil and mix well
14. Serve and enjoy.

This recipe is great through the winter. It is also extra-lovely in the late summer.

To add variation, you can make your own breadcrumbs by pulsing a bakery roll for 10 minutes in your food processor.

Definition \(\tiny{[edit]}\)

The Euclidean distance between points p and q is the length of the line segment connecting them (\(\overline{\textbf{pq}}\)).

In Cartesian coordinates, if p = (\(p_1, p_2,..., p_n\)) and q = (\(q_1, q_2,..., q_n\)) are two points in Euclidean n-space, then the distance (d) from p to q, or from q to p is given by the Pythagorean formula:\(^{[1]}\)

\[\begin{equation} \label{eq:someequation} d(\textbf{p, q}) = \textbf{q, p} = \sqrt{(q_1 - p_1)^2 + (q_2 - p_2)^2 + \ldots + (q_n - p_n)^2} \\ = \sqrt{\sum_{i=1}^{n} (q_i - p_i)^2}. \tag{1} \end{equation}\]

The position of a point in a Euclidean n-space is a Euclidean vector. So, p and q may be represented as Euclidean vectors, starting from the origin of the space (initial point) with their tips (terminal points) ending at the two points. The Euclidean norm, or Euclidean length, or magnitude of a vector measures the length of the vector:\(^{[1]}\)

\[\begin{equation} \| \mathbf{\textbf{p}} \| = \sqrt{p_1^2 + p_2^2 + \ldots + p_n^2} = \sqrt{\textbf{p $\cdot$ p}}, \end{equation}\]

where the last expression involves the dot product.